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Opinion: Shopping online probably won’t save you money

Online prices are generally the same as prices in the store, survey finds

By

AlbertoCavallo

If you’re a bargain hunter, it’s common to spend time researching prices before making purchases. After all, you wouldn’t want to buy a washing machine at your local Lowes store only to find a lower price offered on Lowes.com. However, I found in a recent study that retailers’ offline and online prices are the same more than 70% of the time.

That’s good news for consumers, who don’t need to worry about price comparisons when deciding whether to use a retailer’s website or visit a local store. They can choose instead based on other factors like convenience and product availability.

This finding is important for economists too. Online prices are increasingly being used in measurement and research applications, including studies of pricing behaviors, price stickiness, international relative prices, and exchange-rate dynamics. Many national statistical offices are even considering the use of online data in official consumer price Indexes.

There are good reasons for using online prices: they are easy to collect on a large scale and can provide huge data sets to test economic theories. It is extremely difficult and expensive to collect similar data on in-store prices.

But as we increasingly use online prices, a fundamental question is whether they are indeed similar to the prices that can be obtained offline. After all, online sales are still less than 10% of all retail transactions in the U.S.

To answer this question, I conducted the first large-scale comparison of online and offline prices in large multichannel retailers. I chose multichannel retailers, which sell both online and in physical stores, as they still concentrate the vast majority of retail transactions. I did not include online-only retailers like Amazon
AMZN, -0.13%
and Ebay
EBAY, +0.19%
because they currently represent a small percentage of retail transactions in most countries.

Using a combination of crowdsourcing platforms, a mobile phone app, and webscraping methods, I collected prices in both the online and offline stores of 56 of the largest retailers in 10 countries: Argentina, Australia, Brazil, Canada, China, Germany, Japan, South Africa, the United Kingdom, and the U.S.

I compared price levels, the behavior of price changes, and the selection of products available for sale in the offline and online stores.

The scale of the data collection in this project is unprecedented and was carried out as part of the MIT Billion Prices Project (BPP). I used crowdsourcing platforms like Amazon Mechanical Turk, Elance, and UpWork to hire over 370 workers to collect the offline prices. Each worker was tasked with scanning the barcodes and collecting prices for a random set of 10 to 50 products in any physical store of a given retailer.

All workers used a special BPP app developed specifically to simplify and standardize the data-collection process. Once collected, prices were sent to the BPP servers so we could immediately compare them to the online prices for those same items.

The results were surprising. Contrary to popular belief, online and offline prices were identical about 72% of the time, as shown in the table below. The prices were more similar in apparel and electronics than in some other sectors like drug stores and office supplies.

This is probably because customers can see the price of a TV at each store location and online — and it would be hard to explain any price differences to customers. So someone living in a remote location, for example, pays about the same price as someone living in a large city whether they shop online or in the physical store.

The percentage of similar prices varied by country, ranging from 42% in Brazil to 91% in Canada and the U.K. The U.S. was the closest to the average at 69%. In countries with higher online prices like Brazil, Argentina, and Australia, it’s possible that retailers expect online buyers to have higher incomes and are able to afford the higher prices — or the delivery cost is built into the price.

The degree of price difference seems to depend on the state of development of a country’s offline and online markets.

Interestingly, I saw no evidence that retailers try to obfuscate price comparison by changing the products’ ID numbers or that they try to price discriminate based on location or browsing habits. In the U.S., it is clear that retailers are not varying their prices with the location of the IP address of the computer connecting to the website or when the scraping robot repeatedly browses the same webpage of a particular good over a long period of time.

The results of this study are significant for researchers and statistical agencies, as they show that large multichannel retailers generally price the same offline and online. The ability to collect massive amounts of prices cheaply and quickly provides unprecedented opportunities for economic research. Further, it implies that online prices can be used for consumer price indexes.

It’s also reassuring for consumers, as the web has helped to equalize prices within retailers. There still may be price differences among different retailers (Target
TGT, +0.07%
vs. Walmart
WMT, +0.30%
), but shoppers at Target don’t need to worry about being charged different prices based on their decision to shop online or at a specific Target location. That TV will cost roughly the same no matter whether it’s purchased at Target.com or a bricks and mortar Target store.

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